quality - ct 7
lolo1339
135-526-1-PB.pdf
Submitted: March 2, 2015 Accepted: April 29, 2015
23
Journal of Health Informatics in Developing Countries
www.jhidc.org
Vol. 9 No. 1, 2015
Electronic Medical Record Systems in
Saudi Arabia: Knowledge and Preferences
of Healthcare Professionals
Rihab A. HASANAINa,1, Kirsten VALLMUURb and Michele CLARK a a
School of Clinical Sciences, Queensland University of Technology, Brisbane,
Queensland, Australia b
School of Psychology and Counselling, Queensland University of Technology,
Brisbane, Queensland, Australia
Abstract. Background: The use of Electronic Medical Record (EMR) systems is increasing
internationally, though developing countries, such as Saudi Arabia, have tended to lag behind in the adoption and implementation of EMR systems due to several
barriers. The literature shows that the main barriers to EMR in Saudi Arabia are
lack of knowledge or experience using EMR systems and staff resistance to using
the implemented EMR system.
Methods: A quantitative methodology was used to examine health personnel
knowledge and acceptance of and preference for EMR systems in seven Saudi public hospitals in Jeddah, Makkah and Taif cities.
Results: Both English literacy and education levels were significantly correlated
with computer literacy and EMR literacy. Participants whose first language was not Arabic were more likely to prefer using an EMR system compared to those
whose first language was Arabic.
Conclusion: This study suggests that as computer literacy levels increase, so too do staff preferences for using EMR systems. Thus, it would be beneficial for hospitals
to assess English language proficiency and computer literacy levels of staff prior
to implementing an EMR system. It is recommended that hospitals need to offer training and targeted educational programs to the potential users of the EMR
system. This would help to increase English language proficiency and computer
literacy levels of staff as well as staff acceptance of the system.
Keywords. Electronic Medical Record; Saudi Arabia; English language;
Computer literacy level; Barriers; Implementation.
1. Introduction
Electronic Medical Record (EMR) is considered an essential component of any
healthcare organization.1 Healthcare providers such as physicians and nurses spend
long periods of time during their workday collecting information from patients.2
Examples of the sorts of data collected are demographic information, medical history
and prescribed medication use.2 Some developed countries such as the United Kingdom
and Canada have a national EMR system.3 On the other hand, developing countries
have tended to lag behind in the adoption and implementation of Health Information
Systems (HIS) such as EMR systems, or even a basic EMR system.3 The literature
indicates that EMR systems implementation is limited and at times spasmodic in
1 Corresponding Author.
24
developing as well as low-income countries, largely because of the financial and
implementation challenges these countries face.4 These challenges are likely due to
technological, organizational, financial or human resources barriers.4,5
In Saudi Arabia, initiatives for implementing HIS such as EMR systems have been
occurring over the last three decades.6,7 As well as funds to assist EMR
implementation, the Saudi Ministry of Health (MOH) has made clear its intention to
implement HIS nation-wide.6 Previous research has shown that to date, HIS
implementation is low within Saudi public hospitals, because Saudi Arabia is a
developing country.8 However, it is noted that there are a number of major hospitals
and healthcare organizations that have attained distinguished achievement in EMR
implementation in Saudi Arabia, such as National Guard Health Affair (NGHA)
hospitals, the Armed Forces hospitals and the King Faisal Specialist Hospital and
Research Centre (KFSH & RC).7,9 For example the NGHA hospital system was
awarded the Middle East Excellence Award in electronic health records.10 It is
noteworthy that these health facilities are outside the Saudi public hospital system.11
Previous research in the area of EMRs in Saudi Arabia has shown that the reasons
for such low uptake of EMR implementation in its hospitals is due to a number of
identified barriers.12,13 Two of the main EMR barriers are a lack of knowledge or
experience using EMR systems, and staff resistance to using the implemented EMR
system.11 These barriers have also been found in several other developed and
developing countries, where poor if not non-existent computer literacy is one of the
more common barriers to EMR adoption.14 Thus, this research aims to specifically
examine health personnel’s knowledge and acceptance of and preference for EMR
systems in public hospitals in the western region of Saudi Arabia.
2. Objectives
This research aims to examine both the knowledge and preferences of current or
potential EMR users, at seven hospitals in three cities, within the western region of
Saudi Arabia. The research also aims to identify whether health personnel preference,
in respect to using EMR systems, differs based on a number of aspects, including job
category, English language, and computer and EMR literacy levels. Such findings may
assist future implementation initiatives by informing EMR implementation plans as
well as the staff recruitment policies of hospitals. In addition, the research aims to
identify whether health personnel preference and acceptance, in respect to using EMR
systems, differs amongst small, medium and large sized hospitals.
3. Methodology
A cross-sectional study tool was developed to collect data from seven hospitals in three
cities in Saudi Arabia. The study used a researcher developed quantitative
questionnaire, which was available in both online and paper-based formats.
Questionnaire development was guided and structured by a key reference.15 When
developing the questionnaire, the researchers took into account the literature
concerning EMR implementation, barriers and facilitators as well as knowledge of
25
EMRs in Saudi Arabia gained by the first author through previous work and research
experience. Ethical approval for the study was obtained from the Queensland
University of Technology (QUT), Australia. Approval to distribute the questionnaire in
Saudi Arabia was also obtained from the Director of Health Affairs, Makkah region at
the Saudi Ministry of Health.
3.1 The research instrument
The questionnaire comprised three sections. The first section sought general socio-
demographic information such as participant age, gender and professional background.
Participants were asked to indicate their computer and English language literacy levels.
The second section contained questions about EMR barriers while the third section
focused on EMR implementation. Together with an information sheet and a consent
form, questionnaires were distributed to the seven selected hospitals. The term
Electronic Health Record (EHR) was used in the questionnaire to refer to any HIS
available in the hospital.
3.2 Study population
A total of 480 questionnaires were distributed in the seven selected hospitals and 333
participants completed the survey, giving an effective response rate of 69%. All
participants remained anonymous and voluntarily completed the questionnaire.
Participants of this research included different healthcare personnel such as physicians,
pharmacists, nurses, administration staff, laboratory staff and receptionists all of whom
either use or are likely to use an EMR.
3.3 Participating hospitals
Questionnaires were distributed in seven public hospitals in Jeddah, Makkah and Taif
cities, all located within the western region of Saudi Arabia. For the purpose of this
research, hospital size was categorized based on bed capacity ranging from small (<250
beds), to medium (250-450 beds) and large (>450 beds). Table 1 shows the number of
questionnaires distributed in each hospital together with associated response rates
according to hospital size.
Table 1. Response rates, hospital location and size
Hospital Size
(Bed capacity)
City
Hospital
Bed
capacity
Number of
Distributed
Questionnaires
Number of
Respondents
Small
(<250 beds)
Jeddah
Makkah
Hospital E
Hospital H
83
162
30
30
22 (6.6%)
26 (7.8%)
Medium
(250-450 beds)
Jeddah
Makkah
Hospital C
Hospital G
276
261
60
60
48 (14.4%)
36 (10.8%)
Large
(>450 beds)
Jeddah Makkah
Taif
Hospital A Hospital F
Hospital J
792 493
454
120 90
90
78 (23.4%) 52 (15.6%)
71 (21.3%)
Total 480 333 (69.4%)
26
3.4 Study design
Questionnaires were distributed and collected between November 2011 and January
2012. Participants had the option of completing the questionnaire in either Arabic or
English. Additionally, an online link was provided to all participants, should any prefer
to complete an online version of the questionnaire.
3.5 Statistical analysis
The researchers primarily used SPSS software version 22, for all frequencies and
descriptive analyses. The descriptive analyses were conducted by performing a number
of different tests to identify relationships between variables and to make comparisons
where applicable, such as Spearman’s correlation, chi-square and t-tests.
4. Methodology
4.1 Characteristics of respondents
A total of seven public hospitals in the western region of Saudi Arabia were included in
this study. Overall, 333 completed questionnaires were obtained, and all were in the
written form of the questionnaire. The overall response rate was 69%. Details about the
demographic distribution of participants are presented in Table 2. Table 2 highlights
that the majority of participants (68.4%) were between the ages of 20 and 39 years.
Most of the participants were graduates with either a diploma (38.1%) or bachelor
degree (37.8%). Four-fifths of the participants, (80%) had Arabic as their first
language.
Table 2. Participant demographics (n = 333)
Variable n %
Gender Female
Male
178
155
53.5
46.5
Age Group 20 – 29
30 - 39
40 - 49 50 - 59
60 – 69
111
117
75 29
1
33.3
35.1
22.5 8.7
.3
Highest Education level High School Diploma
Bachelor
Master Doctorate
27 127
126
41 21
8.1 38.1
37.8
12.3 3.6
Position At Work Laboratory Staff
Receptionist
Pharmacist
Nurse
Physician
Administrator Other
43
18
13
105
83
59 12
12.9
5.4
3.9
31.5
24.9
17.7 3.6
27
Variable n %
Is Arabic Your First
Language?
No Yes
64 269
19.2 80.8
Your English Language
Level
Poor
Fair Good
Excellent
42
88 139
64
12.6
26.4 41.7
19.2
Computer Literacy
Poor
Fair Good
Excellent
45
68 145
75
13.5
20.4 43.5
22.5
EMR Literacy Poor Fair
Good
Excellent
35 74
99
26
10.5 22.2
29.7
7.8
4.2 Education, English language, computer and EMR system literacy levels
Spearman’s correlation was used to examine the relationship between self-reported
computer literacy, self-reported EMR literacy, self-reported English language
proficiency level and education level. Results indicate that English proficiency level
was highly correlated with computer literacy and EMR literacy, rs = 0.44, p < .001 and
rs = .31, p < .001 respectively.
Education level was also highly correlated with computer literacy and EMR
literacy, rs = .29, p < .001 and rs = .18, p = .005. It is noted that education level was not
treated as a continuous variable. Thus, Spearman’s correlation was used. This analysis
was thought to be suitable because it retains the ordinal structure of the variable,
whereas using ANOVA would lose the information in the ordinal structure.
Spearman’s correlation was used to examine the relationship between computer
literacy and EMR literacy. Results indicate that there was a highly significant positive
relationship between computer literacy and EMR literacy, rs (232) = .44, p < .001.
An independent sample t-test was used to examine if there were significant
differences in computer literacy between participants who preferred to use a computer-
based health record compared to those who preferred paper-based health records.
Results indicate that participants who preferred computer-based health records had
significantly higher self-reported computer literacy, t (331) = 4.683, p < .001.
Staff were categorized into two groups namely ‘medical staff’ comprising those
with health professional qualifications and skills such as physicians, pharmacists,
nurses and laboratory staff. The other group, ‘non-medical staff’, comprised
receptionists and administrators. Participants who recorded their job category as
‘Other’ (n=12, 3.6%) and were not included in either group and thus were excluded
from this analysis. Chi-square tests were used to examine the differences between
preferred health record system and job category as well as first language (Table 3).
Results indicate that there was no significant difference between job category and
preferred health record system. However, those participants whose first language was
not Arabic were significantly more likely to prefer using an electronic health record
compared to those whose first language was Arabic (2) = 10.93, p < .001.
A t-test was used to examine any difference in English language level between
participants who either preferred an electronic health record or a paper health record.
Results revealed that participants who preferred electronic health record (M = 2.77, SD
28
= 0.89) had a significantly higher English language level than participants who
preferred to use a paper health record t (331) =4.270, p <.001.
Table 3. Preferred health record system, job category and first language
Electronic Health Record Paper Health Record
2
n= % n= %
Job category
Medical staff
206
84.4
38
15.6
2.47
Non-medical staff 59 76.6 18 23.4
Is Arabic the first
language?
No 62 96.9 2 3.1 10.93***
Yes 214 79.6 55 20.4
4.3 Hospital size and type of preferred health record
Of the 276 respondents who indicated their preferred type of record, approximately
four-fifths (83%) would prefer to use an EMR over paper records. Respondents’
preference for an EMR system rather than paper record were 90% for small hospitals
and 82% respectively for medium and large hospitals.
A chi square test was used to examine any difference between hospital size and
preferred type of health record, but failed to reach significance (2) = 1.79, p = .426.
5. Discussion
A small number of studies have examined the implementation of EMR systems in
Saudi Arabia, and identified a range of barriers.7,10,12 It was noted that the main barriers
obstructing EMR implementation were lack of knowledge and experience using EMR
systems; and staff resistance to using the system.10,11 The present study adds to this
body of knowledge by looking further at the lack of knowledge about and experience
with using EMR systems among hospital staff in Saudi Arabia. Also, the study
examined staff attitudes in respect of their preferences for EMR systems, and whether
these preferences differ according to hospital size. The study yielded a number of main
findings.
There was a significant positive correlation between English language proficiency
level and computer literacy and EMR literacy levels. Additionally, the study results
show that there is a significant correlation between education level and computer and
EMR literacy levels. Thus use of and preference for EMR systems appears to be related
to socio-economic determinants such as educational level, English language
proficiency and computer literacy.
Moreover, other socio-demographic factors may be contributing to EMR barriers.16
For example, Arabic language was the first language of over three-quarters (80%) of all
participants. However most of the EMR systems are in English language,17 and yet
Arabic is the first language in Saudi Arabia. Since English language proficiency level
29
is significantly associated with computer literacy level and preferred health record
system (electric health record rather than paper health record), it would appear
important to have healthcare personnel who are literate in the English language in order
to maximize the effective use of the system within Saudi public hospitals.16
By improving the overall English language proficiency and computer literacy
levels of staff, it is likely that their EMR literacy level would improve. Thus, staff
would be more able to use EMR systems, and the acceptance level would likely
increase as well.16 By providing training or through recruiting staff with the requisite
knowledge and skills one of the main barriers to EMR implementation in Saudi public
hospitals could be overcome. The results highlight the importance of having well-
trained staff who have the required level of computer literacy for EMR adoption for
hospitals seeking to implement EMR systems in Saudi Arabia.18
Our findings have encouraging implications for hospitals wanting to increase EMR
user acceptance levels in Saudi Arabia. The vast majority of participants of this study
preferred the use of electronic based health records over paper based health records.
However, the questionnaire findings also suggest that participants who preferred to use
electronic based health records had significantly higher education and computer
literacy levels. Once again, the study shows that increasing computer literacy levels
amongst staff could increase the acceptance of and preference levels for using EMR
systems. Thus, there is a need to provide computer training sessions for potential users
and/or users who are facing difficulties using the system.19 An alternative or
complementary strategy would be to recruit new staff who have the appropriate
educational and computer competencies. Despite the large number of participants
indicating a preference for electronic records, it is paradoxical that no participants
opted to complete their survey electronically.
Overall the findings of the current study are in keeping with previous research.
Previous research also found that computer literacy is a major factor for increasing user
acceptance of EMRs.20,21 Similarly language issues such as poor English proficiency
levels have been reported as one of the barriers to EMR implementation in developing
countries.22 Studies have also shown that low computer literacy is one of the themes of
dissatisfaction in organizations that are implementing Information Technology (IT)
systems.14 Additionally, a positive correlation was found in previous research between
users’ positive attitude towards the system and computer literacy.14 These finding
highlight the importance of considering computer literacy issues prior to implementing
EMR systems, in order to increase user acceptance for adopting EMR systems in Saudi
hospitals.14
The current study found no relationship between preference for type of health
record system and hospital size. This finding was surprising given that a number of
studies have shown that firm size usually has a positive impact on organizations when
implementing new technologies.8,23,24 Firm size is thought to impact the
implementation of new technology as large organizations potentially have more
resources to invest in planning and training than medium and small healthcare
organizations.1 Studies have also indicated that hospital characteristics may differ
between different sized hospitals, such as location, services provided and the number of
the available clinical IT systems.23,25 The current study had seven participating
hospitals in one province and therefore further research is needed with staff from a
larger number of hospitals to investigate any possible association between hospital size
and preferred health record system.
30
The study had a number of limitations. Firstly, the study examined seven hospitals
in one region of Saudi Arabia. Thus the findings may not be representative of public
hospitals in other areas of Saudi Arabia. Any attempt to generalize from the findings
would need to be done with caution. Secondly, the findings of this study were based on
self-report and could have been open to some response bias. The participants self-
selected to complete the questionnaire, and thus it is possible that there was some
selection bias. For example, it is possible that those with better computer skills or with
more familiarity with EMR completed the survey.
6. Conclusion
User acceptance is one of the key factors for success in EMR implementation.26 In
Saudi Arabia, there is a lack of knowledge about the use of EMR systems amongst a
range of health professional and administrative staff. Findings of this current study
suggest that as computer literacy levels increase, so too do staff preferences for using
EMR systems. While staff attitudes are favorable towards using EMR they may lack
the English language and computer literacy skills that are a foundation to using EMR’s.
Results of this study also show that hospital size is not associated with staff preference
for EMR systems over paper-based systems. These finding may assist policy makers
who are seeking to develop and implement such systems in Saudi Arabia.25 The vast
majority of healthcare personnel in Saudi public hospitals prefer the use of an
electronic based health record system, such as EMRs, regardless of the size of the
hospital in which they work.
Based on these findings it is recommended that it would be beneficial for hospitals
seeking to implement EMR system, to assess the English language proficiency and
computer literacy levels of staff prior to the implementation. This would assist in
identifying the sorts of training and educational programs that may be required, in
order to have a more literate staff who could then maximize their use of the system.
Recruitment strategies, in Saudi public hospitals, could also use the information to
ensure that new staff come with the appropriate foundation or enabling skills and
knowledge. Further study using a larger sample size and hospitals from more regions
could examine if there is an association between both English language and computer
literacy levels and hospital size in Saudi public hospitals.
7. Acknowledgements
Rihab Hasanain is the recipient of a full education scholarship from the Saudi
government under King Abdullah international Scholarship program. Some findings of
this study were presented in a poster at the “Engaged Patients: Rebalancing the Clinical
Relationship” conference at the Health Informatics New Zealand (HINZ) conference,
Rotorua, New Zealand 2013.
8. Disclosure
The author reports no conflicts of interest in this work.
31
References
[1] Mitchell S, Yaylacicegi U. Analysis of Electronic Health Record Implementation and Usage in Texas
Acute Care Hospitals. Journal of Information Systems Applied Research 2013;6:49-56.
[2] Conrick M. Health Informatics: Social Science Press, Melbourne; 2006. [3] Sinha PS, G.; Bendale, P.; Mantri, M.; Dande, A. Electronic Health Record:Standards, Coding
Systems, Frameworks, and Infrastructures: Wiley-IEEE Press 2013.
[4] Luna D, Almerares A, Mayan JC, 3rd, Gonzalez Bernaldo de Quiros F, Otero C. Health Informatics in Developing Countries: Going beyond Pilot Practices to Sustainable Implementations: A Review
of the Current Challenges. Healthc Inform Res 2014;20:3-10.
[5] Naseem A, Rashid A, Kureshi NI. E-health: effect on health system efficiency of Pakistan. Ann Saudi Med 2014;34:59-64.
[6] Altuwaijri M. Electronic-health in Saudi Arabia. Just around the corner? Saudi Med J 2008;29:171-8. [7] Hasanain R, Vallmuur K, Clark M. Progress and Challenges in the Implementation of Electronic
Medical Records in Saudi Arabia: A Systematic Review. Health Informatics - An International
Journal 2014;3. [8] Aldosari B. Rates, levels, and determinants of electronic health record system adoption: A study of
hospitals in Riyadh, Saudi Arabia. International Journal of Medical Informatics 2014.
[9] Alkhamis A. Health care system in Saudi Arabia: an overview. East Mediterr Health J 2012;18:1078-9. [10] Hasanain R, Cooper H. Solutions to Overcome Technical and Social Barriers to Electronic Health
Records Implementation in Saudi Public and Private Hospitals. Journal of Health Informatics in
Developing Countries 2014;8. [11] Alanazy S. Factors associated with implementation of electronic health records in Saudi Arabia: D.,
UNIVERSITY OF MEDICINE AND DENTISTRY OF NEW JERSEY, New Jersey, USA.; 2006.
[12] Alkraiji A, Jackson T, Murray I. Barriers to the widespread adoption of health data standards: an exploratory qualitative study in tertiary healthcare organizations in saudi arabia. J Med Syst
2013;37:9895.
[13] Khalifa M. Technical and Human Challenges of Implementing Hospital Information Systems in Saudi Arabia. Journal of Health Informatics in Developing Countries 2014;8.
[14] Huryk LA. Factors influencing nurses' attitudes towards healthcare information technology. J Nurs Manag 2010;18:606-12.
[15] Czaja R, Blair J. Designing surveys: A guide to decisions and procedures: Pine Forge Pr, Thousand OK, CA; 2005.
[16] NORC. Understanding the Impact of Health IT in Underserved Communities and those with Health Disparities. In: Chicago NatUo, ed. Chicago: The United States Department of Health and Human
Services; 2010.
[17] Kimura M, Croll P, Li B, et al. Survey on medical records and EHR in Asia-Pacific region: languages, purposes, IDs and regulations. Methods Inf Med 2011;50:386-91.
[18] Ajami S, Bagheri-Tadi T. Barriers for Adopting Electronic Health Records (EHRs) by Physicians. Acta Inform Med 2013;21:129-34.
[19] Huang Y-H, Garrett S, Taaffe K, Gramopadhye A. Are Staff in Rural Healthcare Facilities Ready for EHRs? In: IIE Annual Conference; 2012; United States: Institute of Industrial Engineers-
Publisher; 2012. p. 1-10. [20] Razzaque A, Jalal-Karim A. Conceptual HealthCare Knowledge Management Model For Adptability
and Interoperability of EHR. In: European, Mediterranean & Middle Eastern Conference on
Information Systems 2010; United Arab Emirates; 2010. [21] McNeil BJ, Elfrink V, Beyea SC, Pierce ST, Bickford CJ. Computer literacy study: report of qualitative
findings. J Prof Nurs 2006;22:52-9.
[22] Omary Z, Lupiana D, Mtenzi F, Wu B. Analysis of the Challenges Affecting E-healthcare Adoption in Developing Countries: A Case of Tanzania. International Journal of Information Studies 2010;2.
[23] Mitchell S, Yaylacicegi U. EHR prescription for small, medium, and large hospitals: an exploratory study of Texas acute care hospitals. Int J Electron Healthc 2012;7:125-40.
[24] Khuspe S. Effects of staffing and expenditure variables on after surgery patient safety in Florida hospitals: University of South Florida; 2004.
[25] Ferrier G, Valdmanis V. Rural hospital performance and its correlates. Journal of Productivity Analysis 1996;7:63-80.
[26] Hochron SM, Goldberg P. Overcoming barriers to physician adoption of EHRs. Healthc Financ Manage 2014;68:48-52.
